The field of the invention is systems and methods for electrophysiology monitoring during magnetic resonance imaging (“MRI”). More particularly, the invention relates to systems and methods for removing magnetic gradient field-induced errors in electrophysiology signals (e.g., electrocardiogram, intracardiac electrocardiogram, electroencephalogram, electromyogram) acquired during the performance of an MRI pulse sequence.
When electrocardiograms (“ECG”) traces are collected within the bore of a magnetic resonance imaging (“MRI”) scanner while MRI images are being acquired, large induced voltages are superimposed on the conventional ECG traces. These voltages arise as a result of the MRI gradient coils, which induce large electrical fields into the human body, which then travel to the surface electrodes. These voltages can be 1000 times more intense than the native ECG (reaching up to 5V peak-to-peak), and as a result, it is frequently difficult to observe the physiologically-based ECG traces (“true ECG”) during the execution of an MRI pulse sequence. This inability to observe the patient's true ECG traces restricts the ability to monitor the patient's physiology, or to properly synchronize the MRI scanner to the ECG, which is required in MRI sequences that are used to study the heart or the cardiovascular anatomy.
Removal of this MRI-gradient-induced voltage is currently (commercially) performed by a combination of several techniques. First, a restricted number (e.g., 4-6) of ECG electrodes are placed very close to each other, and at the center of the bore, in order to minimize the induced voltage. Second, high impedance (e.g., greater than 10 kΩ) transmission lines are typically used to reduce the amplitude of the currents that are generated by the gradient-induced voltages. Third, the received ECG traces are strongly low-pass frequency filtered so as to remove the higher frequency components of the induced voltages. Both of these operations results in ECG traces that are temporally distorted and very low in fidelity (i.e., low in amplitude with high noise content), so that they can be used only for synchronizing the MRI scanner, and not for monitoring the patient condition inside the MRI scanner. As a result, many severely-ill patients are excluded from MRI imaging and from MRI-guided surgical interventions.
For instance, most approaches apply strong low-pass filters of the order of 50 Hz to the ECG traces to remove the high-frequency components in the induced voltages. This approach is limited, however, by the retention of low frequency components of the gradient-induced voltages in the ECG traces, and it leads to distorted waveforms that are less useful for patient monitoring. Adaptive digital filter strategies have been used to reduce the ECG noise by detecting the gradient waveforms generated by the MRI pulse sequences and modeling the noise response as a linear time-invariant system that is convolved with the temporal response of the gradients. Most approaches have assumed that the time-derivates of the gradients are the major contributor, but a systematic derivation of the relationship between the gradients and the induced noise has not been demonstrated.
It would therefore be desirable to provide systems and methods that are capable of removing gradient-induced voltages from electrophysiology signal acquired during an MRI scan while preserving the pertinent information in the electrophysiology signals. For instance, such information may be used by clinicians to detect the onset and nature of several cardiac events to provide appropriate treatment.